Hydrogels with ultrafast response to environmental stimuli, possessing robust structural integrity and rapid self-recovery, have been considered as promising platforms for numerous applications, for ...example, in biomimetic materials and nanomedicine. Inspired by the bundled fibrous structure of actin, we developed a robust and ultrafast thermoresponsive fibrous hydrogel (TFH) by fully utilizing the weak noncovalent bonds and strong covalently cross-linked semiflexible electrospun fibrous nets. The TFH exhibits an ultrafast response (within 10 s), rapid self-recovery rate (74% within 10 s), tunable tensile strength (3–380 kPa), and high toughness (∼1560 J/m2) toward temperature. A multiscale orientation is considered to play a key role in the excellent mechanical properties at the fibrous mesh, fiber, and molecular scales. Furthermore, to take advantage of this TFH adequately, a novel kind of noodle-like hydrogel for thermo-controlled protein sorption based on the TFH is prepared, which exhibits high stability and ultrafast sorption properties. The bioinspired platforms hold promise as artificial skins and “smart” sorption membrane carriers, which provide a unique bioactive environment for tissue engineering and nanomedicine.
Abstract
Despite the accumulating evidence linking the development of Alzheimer’s disease (AD) to the aggregation of Aβ peptides and the emergence of Aβ oligomers, the FDA has approved very few ...anti-aggregation-based therapies over the past several decades. Here, we report the discovery of an Aβ peptide aggregation inhibitor: an ultra-small nanodot called C
3
N. C
3
N nanodots alleviate aggregation-induced neuron cytotoxicity, rescue neuronal death, and prevent neurite damage in vitro. Importantly, they reduce the global cerebral Aβ peptides levels, particularly in fibrillar amyloid plaques, and restore synaptic loss in AD mice. Consequently, these C
3
N nanodots significantly ameliorate behavioral deficits of APP/PS1 double transgenic male AD mice. Moreover, analysis of critical tissues (e.g., heart, liver, spleen, lung, and kidney) display no obvious pathological damage, suggesting C
3
N nanodots are biologically safe. Finally, molecular dynamics simulations also reveal the inhibitory mechanisms of C
3
N nanodots in Aβ peptides aggregation and its potential application against AD.
The comprehensive integration of machine learning healthcare models within clinical practice remains suboptimal, notwithstanding the proliferation of high-performing solutions reported in the ...literature. A predominant factor hindering widespread adoption pertains to an insufficiency of evidence affirming the reliability of the aforementioned models. Recently, uncertainty quantification methods have been proposed as a potential solution to quantify the reliability of machine learning models and thus increase the interpretability and acceptability of the results. In this review, we offer a comprehensive overview of the prevailing methods proposed to quantify the uncertainty inherent in machine learning models developed for various medical image tasks. Contrary to earlier reviews that exclusively focused on probabilistic methods, this review also explores non-probabilistic approaches, thereby furnishing a more holistic survey of research pertaining to uncertainty quantification for machine learning models. Analysis of medical images with the summary and discussion on medical applications and the corresponding uncertainty evaluation protocols are presented, which focus on the specific challenges of uncertainty in medical image analysis. We also highlight some potential future research work at the end. Generally, this review aims to allow researchers from both clinical and technical backgrounds to gain a quick and yet in-depth understanding of the research in uncertainty quantification for medical image analysis machine learning models.
•The first review regarding probabilistic and non-probabilistic uncertainty analysis.•Uncertainty evaluation criteria applied for medical image analysis are studied.•Clinical applications of uncertainty quantification methods are discussed.•The advantages, limitations and potential future work are pointed out.
Metazoan cells only utilize a small subset of the potential DNA replication origins to duplicate the whole genome in each cell cycle. Origin choice is linked to cell growth, differentiation, and ...replication stress. Although various genetic and epigenetic signatures have been linked to the replication efficiency of origins, there is no consensus on how the selection of origins is determined.
We apply dual-color stochastic optical reconstruction microscopy (STORM) super-resolution imaging to map the spatial distribution of origins within individual topologically associating domains (TADs). We find that multiple replication origins initiate separately at the spatial boundary of a TAD at the beginning of the S phase. Intriguingly, while both high-efficiency and low-efficiency origins are distributed homogeneously in the TAD during the G1 phase, high-efficiency origins relocate to the TAD periphery before the S phase. Origin relocalization is dependent on both transcription and CTCF-mediated chromatin structure. Further, we observe that the replication machinery protein PCNA forms immobile clusters around TADs at the G1/S transition, explaining why origins at the TAD periphery are preferentially fired.
Our work reveals a new origin selection mechanism that the replication efficiency of origins is determined by their physical distribution in the chromatin domain, which undergoes a transcription-dependent structural re-organization process. Our model explains the complex links between replication origin efficiency and many genetic and epigenetic signatures that mark active transcription. The coordination between DNA replication, transcription, and chromatin organization inside individual TADs also provides new insights into the biological functions of sub-domain chromatin structural dynamics.
Oligomerization of Pr55
is a critical step of the late stage of the HIV life cycle. It has been known that the binding of IP6, an abundant endogenous cyclitol molecule at the MA domain, has been ...linked to the oligomerization of Pr55
. However, the exact binding site of IP6 on MA remains unknown and the structural details of this interaction are missing. Here, we present three high-resolution crystal structures of the MA domain in complex with IP6 molecules to reveal its binding mode. Additionally, extensive Differential Scanning Fluorimetry analysis combined with cryo- and ambient-temperature X-ray crystallography and GNM-based transfer entropy calculations identify the key residues that participate in IP6 binding. Our data provide novel insights about the multilayered HIV-1 virion assembly process that involves the interplay of IP6 with PIP2, a phosphoinositide essential for the binding of Pr55
to membrane. IP6 and PIP2 have neighboring alternate binding sites within the same highly basic region (residues 18-33). This indicates that IP6 and PIP2 bindings are not mutually exclusive and may play a key role in coordinating virion particles' membrane localization. Based on our three different IP6-MA complex crystal structures, we propose a new model that involves IP6 coordination of the oligomerization of outer MA and inner CA domain's 2D layers during assembly and budding.
Cross-Domain Recommendation has been popularly studied to utilize different domain knowledge to solve the cold-start problem in recommender systems. In this paper, we focus on the Cross-Domain ...Cold-Start Recommendation ( CDCSR ) problem. That is, how to leverage the information from a source domain, where items are 'warm', to improve the recommendation performance of a target domain, where items are 'cold'. It has two main challenges, i.e., (1) how to efficiently reduce the discrepancy between the latent embedding distribution across domains and (2) how to generate more robust and stable cold item embeddings. To address these two challenges, we propose CPKSPA , a cross-domain recommendation framework for the CDCSR problem. CPKSPA contains three modules, i.e., rating prediction module, embedding distribution alignment module, and contrastive augmentation module. To start with, we first utilize the rating prediction module to model user-item interactions. To solve the first challenge, we propose proxy Stein path alignment with typical-subgroup discovering algorithm in the embedding distribution alignment module. To tackle the second challenge, we propose the contrastive augmentation module which adopts contrastive augmentation learning to generate more stable and robust cold item embeddings. Our empirical study on Douban and Amazon datasets demonstrates that CPKSPA significantly outperforms the state-of-the-art models.
Promoting clean energy requires finding the right balance among economic, social and environmental factors as the renewable energy generation technologies are often more costly than the conventional ...ones and imply additional requirements for their operation. Measurement of willingness to pay (WTP) can be a very useful tool for eliciting the possibilities for developing the renewables considering multiple determinants. This approach, indeed, reflects the preferences of energy consumers towards different renewable energy sources (RES) technologies and represents them in monetary terms. In this paper, we present a discrete choice experiment that was applied to gauge the WTP of individual houses owners for different RES micro generation technologies. As regards the theoretical novelty of the research, we account for willingness to share micro-generation technologies. The unlabelled discrete choice experiment has been carried out in Lithuania – a Central and Eastern European country – and thus offers a contribution to scientific discussion on the development of renewables in the region. The mixed logit model was applied in order to account for differences in tastes (preferences). Based on the results of mixed logit model, WTP was estimated for the selected RES micro generation technologies (solar photovoltaic, biomass boilers, solar thermal and micro-wind). The results show that owners of detached houses in Lithuania households are ready to pay for solar energy-based technologies (some 3300 EUR and 1363 EUR per solar panel and solar thermal installations, respectively), whereas the other two options are less desirable. As regards willingness to share, the households did not consider the latter criterion as a significant factor.
•The discrete choice experiment is applied on a sample of detached house owners.•The mixed logit model is estimated.•Willingness to pay for microgeneration technologies in Lithuania is estimated.•The results indicate that solar panels and solar thermal plants are the most preferable.
Background
Dysphagia, or swallowing disorders, has become a growing concern due to the aging population, and health literacy plays a crucial role in active aging. However, the relationship between ...them remains unclear.
Aims
To investigate the association between health literacy and dysphagia among community-dwelling older adults in China.
Methods
A survey was conducted on 4462 older adults aged 65 and above in a community in Yiwu City, China, from May 2021 to January 2022. Swallowing problems were assessed using a 30 ml water swallowing test (WST) and the Eating Assessment Tool-10 questionnaire (EAT-10). The participants' health literacy was evaluated using the Chinese Health Literacy Scale (CHLS). Logistic regression and t tests were employed to measure the association between them.
Results
The prevalence of dysphagia was 5.70% and 7.85% as determined by EAT-10 and 30 ml-WST, respectively. The health literacy level of community-dwelling older adults was 24.4 ± 4.93 (9–45). Participants with dysphagia exhibited lower levels of health literacy (
p
< 0.05). The logistic regression model demonstrated an inverse association between health literacy and dysphagia (OR = 0.94, 95%CI = 0.91–0.96 for EAT-10, and OR = 0.93, 95%CI = 0.92–0.95 for WST). Moreover, this association remained significant even after adjusting for covariates.
Discussion
Older adults with dysphagia have lower levels of health literacy, particularly in terms of their ability to seek medical advice, acquire and evaluate medical information, and access social support resources.
Conclusions
Health literacy is associated with dysphagia among community-dwelling older adults. Effective interventions should be implemented to provide support in terms of both medical services and social support for this population.
The establishment of a three-dimensional velocity field is an essential step in seismic exploration, playing a crucial role in understanding complex underground geological structures. Accurate 3D ...velocity fields are significant for seismic imaging, observation system design, precise positioning of underground geological targets, structural interpretation, and reservoir prediction. Therefore, obtaining an accurate 3D velocity field is a focus and challenge in this field of study. To achieve intelligent interpolation of the 3D velocity field more accurately, we have built a network model based on the attention mechanism, JointA 3DUnet. Based on the traditional U-Net, we have added triple attention blocks and channel attention blocks to enhance dimension information interaction, while adapting to the different changes of geoscience data in horizontal and vertical directions. Moreover, the network also incorporates dilated convolution to enlarge the receptive field. During the training process, we introduced transfer learning to further enhance the network’s performance for interpolation tasks. At the same time, our method is a deep learning interpolation algorithm based on an unsupervised model. It does not require a training set and learns information solely from the input data, automatically interpolating the missing velocity data at the missing positions. We tested our method on both synthetic and real data. The results show that, compared with traditional intelligent interpolation methods, our approach can effectively interpolate the three-dimensional velocity field. The SNR increased to 36.22 dB, and the pointwise relative error decreased to 0.89%.
Objective:
The genetic markers for the detection or treatment of cervical squamous cell carcinoma (CESC) are not yet complete. This study aimed to identify the role of MSMO1 (Alternative name: ...SC4MOL) in the occurrence and development of CESC.
Methods:
We evaluated the significance of MSMO1 expression in CESC by using analysis of a public dataset from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Oncomine and GEPIA2 were used to validate MSMO1 as an independent prognostic factor in CESC. Multiple tools were used to analyze the factors and functions associated with MSMO1, such as methylation, miRNA, and co-expressed genes. Furthermore, TIMER and TISIDB were used to study the relationship between MSMO1 expression and immunization in CESC.
Results:
MSMO1 was highly expressed in tumor specimens and could be used as an independent prognostic factor of CESC (
p
< 0.05). But Casiopeinas chemotherapeutics and p63 loss could reduce the expression of MSMO1. The level of methylation MSMO1 was significantly increased in tumor tissues but there was an insignificant effect on the prognosis. MSMO1 was also closely related to hsa-miR-23a-3p, hsa-miR-23b-3p, hsa-miR-130b-3p, and gene IDI1. Specifically, the expression level of MSMO1 had a significant negative correlation with the infiltration level of CD4
+
T cells, Macrophages, Neutrophils, and DCs in CESC. In addition, GSEA identified differential enrichment in systemic lupus erythematosus, vascular smooth muscle contraction, cytokine receptor interaction, focal adhesion, chemokine signaling pathway, and Leishmania infection pathway in KEGG.
Conclusion:
Our findings provide evidence of the implications of MSMO1 in tumors, suggesting that MSMO1 is a promising prognostic biomarker in CESC.
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